Immune Checkpoint Inhibitor-Induced Pancreatic Injury (ICI-PI) in Adult Cancer Patients: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Immune checkpoint inhibitor-induced pancreatic injury (ICI-PI) is a rare immunotoxicity, with limited data on treatment and long-term outcomes. Methods: PubMed, EMBASE, and Cochrane Library were systematically searched for studies reporting ICI-PI in patients with solid malignancies. ICI-PI was defined as pancreatic inflammation post-ICI exposure, diagnosed via radiologic changes or elevated lipase/amylase levels without other underlying causes. The CTCAE grading system was used. The primary objectives were to assess the frequency, severity, serum abnormalities, management, and long-term outcomes. We conducted a proportional single-arm meta-analysis with a random effects model. Results: The analysis included 25 retrospective studies involving 48,704 patients. Tumor types included thoracic/head and neck (38%), skin (26%), genitourinary/gynecological (18%), gastrointestinal (12%), and others (6%). The median age ranged from 56 to 73 years, with a follow-up from 2.5 to 45.9 months. ICI-PI occurred in 3.60% (95% CI: 1.64–6.28%) of patients, with grade ≥ 3 toxicity in 59.45% (95% CI: 35.32–81.37%). The frequency rates of ICI-PI were 1.99% for CTLA4 inhibitors, 5.01% for PD(L)1 inhibitors, and 7.44% for combination ICI therapy (p < 0.01). The median time to onset from treatment initiation ranged from 30 to 390 days, and symptom resolution ranged from 55 to 84 days. Management included corticosteroids (30.20%), intravenous fluids (22.82%), and hospitalization (30.46%). Chronic complications affected 63.54% (95% CI: 29.03–91.56%), including primarily diabetes mellitus (DM 89.45%; 95% CI: 61.88–100.0%) and exocrine pancreatic insufficiency (EPI 10.55%; 95%: 0.0–38.12%). ICI-PI recurrence occurred in 27.2% of those resuming ICI therapy. The objective response rate was 61.7% (95% CI: 55.08–68.17%). Conclusions: ICI-PI, though infrequent, is severe and predisposes patients to chronic complications, including DM and EPI.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.032 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".